Laminar Security
LLM security & compliance
About Laminar Security
What this tool does and where it fits best.
Platform focused on security and compliance for LLM applications, helping ensure data protection.
Prompts for Laminar Security
Challenges using Laminar Security
Key capabilities
What Laminar Security is actually good at.
Tracing and Observability
OpenTelemetry-based automatic tracing of AI frameworks (LangChain, OpenAI, Anthropic) with just 2 lines of code. Tracks input/output, latency, cost, token count, and provides real-time traces via gRPC for optimal performance.
Dynamic Graph IDE
Graphical user interface to build LLM applications as dynamic graphs. Acts as an integrated development environment where developers can build cyclical flows, route to different tools, and collaborate in real-time. Generates abstraction-free code from graphs.
Evaluation Platform
Build fast and custom evaluators without managing evaluation infrastructure. Run evals on hosted datasets, set up online evaluations using LLM-as-a-judge or custom Python scripts for scalable span labeling.
Data Management Infrastructure
Robust data management with built-in vector search over datasets and files. Data can be ingested into LLMs and LLMs can write back to datasets, creating a self-improving data flywheel. Export production traces to datasets for evaluations and fine-tuning.
Tool details
Core technical and commercial details.
Feature highlights
Details that help this tool stand apart in the directory.
Tracing and Observability
OpenTelemetry-based automatic tracing of AI frameworks (LangChain, OpenAI, Anthropic) with just 2 lines of code. Tracks input/output, latency, cost, token count, and provides real-time traces via gRPC for optimal performance.
Dynamic Graph IDE
Graphical user interface to build LLM applications as dynamic graphs. Acts as an integrated development environment where developers can build cyclical flows, route to different tools, and collaborate in real-time. Generates abstraction-free code from graphs.
Evaluation Platform
Build fast and custom evaluators without managing evaluation infrastructure. Run evals on hosted datasets, set up online evaluations using LLM-as-a-judge or custom Python scripts for scalable span labeling.
Data Management Infrastructure
Robust data management with built-in vector search over datasets and files. Data can be ingested into LLMs and LLMs can write back to datasets, creating a self-improving data flywheel. Export production traces to datasets for evaluations and fine-tuning.
Hosted Deployment
Graph pipelines can be hosted directly on Laminar's infrastructure and exposed as scalable API endpoints. Uses RabbitMQ for message queue, Postgres for data, and Clickhouse for analytics.
Browser Agent (Index)
State-of-the-art open-source browser agent that can autonomously perform complex web tasks. Automatically records high-quality browser sessions and syncs them with agent traces for debugging.
Playground Integration
Open LLM spans in the Playground to experiment with prompts and models. Enables quick iteration and testing of different configurations without modifying code.
Labeling Queues
Quickly label data and create evaluation datasets through organized queues. Streamlines the dataset creation process for improving model performance.